Advancements in intelligent transportation systems and communication technology could
considerably reduce delay and congestion through an array of networkwide traffic control …

The random nature of traffic conditions on freeways can cause excessive congestion and
irregularities in the traffic flow. Ramp metering is a proven effective method to maintain …

To develop the most appropriate control strategy and monitor, maintain, and evaluate the
traffic performance of the freeway weaving areas, state and local Departments of …

Recent advances in deep reinforcement learning have shown promising results in solving
sophisticated control problems with high dimensional states and action space. Inspired by …

Recently, with increasing urban traffic congestion, there has been an upsurge in studies on
reinforcement learning for traffic signal control (RL-TSC), which enables efficient traffic …

The trend of increasing traffic demand is causing congestion on existing urban roads,
including urban motorways, resulting in a decrease in Level of Service (LoS) and safety, and …

Traditional control methods may not be adaptive enough for ever-changing traffic dynamics.
Hence, extensive deep reinforcement learning (DRL) methods have been utilized to solve …

Perimeter metering control has long been an active research topic since well-defined
relationships between network productivity and usage, that is, network macroscopic …

Urban traffic corridors are often controlled by more than one agency. Typically in North
America, a state of provincial transportation department controls freeways while another …

The steadily increasing numbers and lengths of traffic jams on freeways have led to the
application of Dynamic Traffic Management (DTM) measures all over the world. Ramp …